• DocumentCode
    599226
  • Title

    Mining the associations between pharmic quality and ingredients of traditional Chinese medicines

  • Author

    Xia Wu ; Hui-jin Wang ; Guo-ming Chen ; Wei-heng Zhu ; Shun Long

  • Author_Institution
    Dept. of Comput. Sci., JiNan Univ., Guangzhou, China
  • fYear
    2012
  • fDate
    4-7 Oct. 2012
  • Firstpage
    480
  • Lastpage
    485
  • Abstract
    This paper presents our works to tackle three key problems in modern research of traditional Chinese medicines. Based on a dataset of 100 medicines (each with 60 major ingredients), we evaluate various data mining approaches in order to unveil the underlying associations between these chemical ingredients and the pharmic qualities of the medicines. Based on our experiements, we conclude that these associations do exist and can be effectively unveiled. Various performance enhancement techniques are then evaluated, among which we identify the best classification approach for practice. These unveiled associations between pharmic quality and ingredients of traditional Chinese medicine can help guide future researches in this area, particularly in the development of new medicines.
  • Keywords
    data mining; medical computing; pattern classification; pharmaceuticals; quality control; associations mining; chemical ingredients; classification approach; data mining; performance enhancement techniques; pharmic quality; traditional Chinese medicine ingredients; Accuracy; Association rules; Bayesian methods; Chemicals; Decision trees; Medical diagnostic imaging; Chemical Ingredients; Data Mining; Pharmic Quality Analysis; Traditional Chinese Medicine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine Workshops (BIBMW), 2012 IEEE International Conference on
  • Conference_Location
    Philadelphia, PA
  • Print_ISBN
    978-1-4673-2746-6
  • Electronic_ISBN
    978-1-4673-2744-2
  • Type

    conf

  • DOI
    10.1109/BIBMW.2012.6470368
  • Filename
    6470368